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On the Relationship between Local Rewiring Rules and Stationary Out-degree Distributions in Adaptive Random Boolean Network Models

by Taichi Haruna, Sayaka Tanaka
"... We discuss the relationship between local rewiring rules and stationary out-degree distributions in adaptive random Boolean network models that evolve toward criticality. We derive a theoretical formula for the relationship via a master equation approach. The theoretical result is shown to agree wel ..."
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We discuss the relationship between local rewiring rules and stationary out-degree distributions in adaptive random Boolean network models that evolve toward criticality. We derive a theoretical formula for the relationship via a master equation approach. The theoretical result is shown to agree

Out−degree

by Mika Gustafsson, Anna Lombardi
"... • Infer linear “gene-to-gene ” networks from “extended Spellman ” data (yeast cell-cycles) of expression levels and rates. • Classical underdetermined linear regression problem (6178 genes and 73 measurements). We infer networks from these genes and from a subset of 327 genes proposed by de Lichtenb ..."
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the bio-logical aspects of the networks. Some network properties • Broad out-degree distribution (see fig-ure) • Narrow in-degree distribution (de-sired, but probably due to the LASSO) • Excess of transcription factors among the hubs (Gustafsson et al 2004)

Table of Contents

by unknown authors
"... In- and Out-Degree Distribution in the E. coli Transcription-Regulatory Network..............................3 ..."
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In- and Out-Degree Distribution in the E. coli Transcription-Regulatory Network..............................3

NONSTANDARD REGULAR VARIATION OF IN-DEGREE AND OUT-DEGREE IN THE PREFERENTIAL ATTACHMENT MODEL

by Gennady Samorodnitsky, Sidney Resnick, Don Towsley, Richard Davis, Amy Willis, Phyllis Wan
"... Abstract. For the directed edge preferential attachment network growth model studied by Bol-lobás et al. (2003) and Krapivsky and Redner (2001), we prove that the joint distribution of in-degree and out-degree has jointly regularly varying tails. Typically the marginal tails of the in-degree dis-tri ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
Abstract. For the directed edge preferential attachment network growth model studied by Bol-lobás et al. (2003) and Krapivsky and Redner (2001), we prove that the joint distribution of in-degree and out-degree has jointly regularly varying tails. Typically the marginal tails of the in-degree dis-tribution

Graphs over Time: Densification Laws, Shrinking Diameters and Possible Explanations

by Jure Leskovec, Jon Kleinberg, Christos Faloutsos , 2005
"... How do real graphs evolve over time? What are “normal” growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs, identifying properties in a single snapshot of a large network, or in a very small number of snapshots; these include hea ..."
Abstract - Cited by 541 (48 self) - Add to MetaCart
heavy tails for in- and out-degree distributions, communities, small-world phenomena, and others. However, given the lack of information about network evolution over long periods, it has been hard to convert these findings into statements about trends over time. Here we study a wide range of real graphs

Statistics of citation networks Typeset using REVT E X 1

by Alexei Vazquez
"... Abstract The out-degree distribution of citation networks is investigated. Statistical data of the number of papers cited within a paper (out-degree) for different journals in the period 1991-1999 is reported. The out-degree distribution is characterized by a maximum at intermediate out-degrees. At ..."
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Abstract The out-degree distribution of citation networks is investigated. Statistical data of the number of papers cited within a paper (out-degree) for different journals in the period 1991-1999 is reported. The out-degree distribution is characterized by a maximum at intermediate out-degrees

Statistics of Citation Networks

by Alexei Vazquez - Physics E-Print Archive: arXiv:cond-mat/0105031 (http://arxiv.org/abs/cond-mat/0105031 , 2001
"... The out-degree distribution of citation networks is investigated. Statistical data of the number of papers cited within a paper (out-degree) for different journals in the period 1991-1999 is reported. The out-degree distribution is characterized by a maximum at intermediate out-degrees. At the left ..."
Abstract - Cited by 12 (0 self) - Add to MetaCart
The out-degree distribution of citation networks is investigated. Statistical data of the number of papers cited within a paper (out-degree) for different journals in the period 1991-1999 is reported. The out-degree distribution is characterized by a maximum at intermediate out-degrees. At the left

Directed scale-free graphs.

by Béla Bollobás , Christian Borgs , Jennifer Chayes , Oliver Riordan - In SODA’03, , 2003
"... Abstract We introduce a model for directed scale-free graphs that grow with preferential attachment depending in a natural way on the in-and out-degrees. We show that the resulting in-and out-degree distributions are power laws with different exponents, reproducing observed properties of the worldw ..."
Abstract - Cited by 76 (5 self) - Add to MetaCart
Abstract We introduce a model for directed scale-free graphs that grow with preferential attachment depending in a natural way on the in-and out-degrees. We show that the resulting in-and out-degree distributions are power laws with different exponents, reproducing observed properties

Graph evolution: Densification and shrinking diameters

by Jure Leskovec, Jon Kleinberg, Christos Faloutsos - ACM TKDD , 2007
"... How do real graphs evolve over time? What are “normal” growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs, identifying properties in a single snapshot of a large network, or in a very small number of snapshots; these include hea ..."
Abstract - Cited by 267 (16 self) - Add to MetaCart
heavy tails for in- and out-degree distributions, communities, small-world phenomena, and others. However, given the lack of information about network evolution over long periods, it has been hard to convert these findings into statements about trends over time. Here we study a wide range of real graphs

Microscopic Evolution of Social Networks

by Jure Leskovec , Lars Backstrom, Ravi Kumar, Andrew Tomkins , 2008
"... We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at such a large scale, we study individual node arrival and edge creation processes that collectively lead to macroscopic pr ..."
Abstract - Cited by 206 (10 self) - Add to MetaCart
triangle-closing model free of any parameters. We show analytically that the combination of the gap distribution with the node lifetime leads to a power law out-degree distribution that accurately reflects the true network in all four cases. Finally, we give model parameter settings that allow automatic
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